The present invention relates generally to error correction technology. More particularly, the invention relates to an iterative decoding method and apparatus that use certain statistical characteristics derived from a number of check nodes not satisfying a parity check equation, and a number of error bits. The present invention also relates to recording medium having recorded thereon a computer program which when executed implements the foregoing iterative decoding method.
Iterative decoding algorithms have been used for many decades in various technical applications. Consider for example the well known iterative decoding algorithm proposed by Gallager in 1962. In the Gallager and similar type iterative decoding algorithms, a parity check operation is performed on a codeword “c”, where the parity-checked codeword “c” satisfies a parity check equation, such as (e.g.), H·cT=0, where H denotes a parity check matrix, and cT denotes a transpose matrix for the codeword “c” updated every iterative decoding cycle. The parity check operation is performed by repeated update through (or up to) a predetermined number of update cycles (or iterations).
The phrase “up to” is used in the above description because an iterative decoding algorithm may be completed (or resolved) before a predetermined, maximum number (“N”) of iterative cycles has been executed. On the other hand, there are certain circumstances wherein the maximum number of update cycles will be executed before resolution of the iterative decoding algorithm. In such circumstances where the iterative decoding algorithm does not reach resolution before the maximum number of iterative decoding cycles has been reached, a “last or Nth codeword” stored in memory locations designated for iterative computational results, hereafter terms “variable nodes”, is output as a final decoding result. In some applications or circumstances, such an “Nth codeword as final decoding result” outcome may be sufficient. However, other outcomes may arise.
For example, if a corresponding bit error rate for the data being iteratively decoded generally decreases with an increasing number of iterative decoding cycles, but then increases upon execution of the last (Nth) iterative decoding cycle, then the bit error rate associated with Nth iterative decoding cycle may actually exceed a predefined minimum bit error rate. Thus, it is possible for a constituent iterative decoding algorithm to exhibit excellent performance characteristics during its execution, and yet result in an error-floor phenomenon wherein late stage (or last stage) performance improvements abruptly slowed given a high signal-to-noise ratio (SNR) environment. This type of error-floor phenomenon limits the overall utility of the iterative decoding algorithm.